A company wants to create an AI solution to generate images and descriptions for a product catalog. The company needs to select a foundation model (FM) for this solution.The company must consider the output types of each FM.Which FM characteristic is the company evaluating?
Answer(s): D
Modality refers to the types of input and output data a foundation model can handle, such as text, images, or both. Evaluating modality ensures the selected FM can generate both images and text descriptions for the product catalog.
A hospital wants to use a generative AI solution with speech-to-text functionality to help improve employee skills in dictating clinical notes.Which AWS service meets these requirements?
AWS HealthScribe is specifically designed for healthcare workflows, providing accurate speech-to-text transcription of clinical conversations and generating structured clinical notes, meeting the hospital’s need to improve employee dictation of clinical documentation.
A company is using domain-specific models. The company wants to avoid creating new models from the beginning. The company instead wants to adapt pre-trained models to create models for new, related tasks.Which ML strategy meets these requirements?
Answer(s): B
Transfer learning allows the company to adapt pre-trained models for new, related tasks, saving time and resources compared to training models from scratch. The other options do not address the goal of reusing existing models.
A company wants to keep its foundation model (FM) relevant by using the most recent data. The company wants to implement a model training strategy that includes regular updates to the FM.Which solution meets these requirements?
Continuous pre-training keeps a foundation model “always learning” by periodically (or even continuously)ingesting the latest data and updating its weights. This approach ensures the model stays current without having to start training from scratch every time new data arrives, unlike static or strictly batch-oriented methods.
A company has trained a foundation model (FM) to perform a specific task. The company needs to fine-tune the FM to perform a different but related task.Which fine-tuning method will meet this requirement?
Answer(s): C
Transfer learning adapts an already trained foundation model to a new but related task by leveraging the knowledge learned from the original task, reducing training time and data requirements while improving performance.
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